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논문 기본 정보

자료유형
학술저널
저자정보
이다운 (Kumoh National Institute of Technology) 손정우 (Kumoh National Institute of Technology)
저널정보
한국소음진동공학회 한국소음진동공학회논문집 한국소음진동공학회논문집 제30권 제5호(통권 256호)
발행연도
2020.10
수록면
497 - 505 (9page)
DOI
10.5050/KSNVE.2020.30.5.497

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초록· 키워드

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In the present work, a novel method to control the motion of mobile robot remotely using hand gesture recognition technique is proposed. The mobile robot moves or performs a predefined action according to the recognized user’s hand gesture. For the training and test data of machine learning algorithm, electromyogram (EMG) signals for six kinds of hand gestures were measured by using a commercial wearable EMG measurement device. After signal processing, feature vectors were obtained from the measured EMG signals for hand gestures. One hundred measurements were conducted for each hand gesture and 80 % and 20 % of obtained data were used for training and test, respectively. The artificial neural network was designed for the gesture classification and the classification accuracies were evaluated according to numbers of hidden neurons. After assembling a mobile robot by miniaturizing industrial folk lift, the performance of the proposed method was evaluated in real-time environment. It is effectively demonstrated that the proposed method has a great potential for tele-manipulation of mobile robot with high classification accuracy.

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ABSTRACT
1. 서론
2. 근전도 측정
3. 손동작 인식
4. 모바일 로봇 제어
5. 결론
References

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UCI(KEPA) : I410-ECN-0101-2020-424-001285818